abstract: The ability to tolerate bouts of oxygen deprivation varies tremendously across the animal kingdom. Adult humans from different regions show large variation in tolerance to hypoxia; additionally, it is widely known that neonatal mammals are much more tolerant to anoxia than their adult counterparts, including in humans. Drosophila melanogaster are very anoxia-tolerant relative to mammals, with adults able to survive 12 h of anoxia, and represent a well-suited model for studying anoxia tolerance. Drosophila live in rotting, fermenting media and a result are more likely to experience environmental hypoxia; therefore, they could be expected to be more tolerant of anoxia than adults. However, adults have the capacity to survive anoxic exposure times ~8 times longer than larvae. This dissertation focuses on understanding the mechanisms responsible for variation in survival from anoxic exposure in the genetic model organism, Drosophila melanogaster, focused in particular on effects of developmental stage (larval vs. adults) and within-population variation among individuals. Vertebrate studies suggest that surviving anoxia requires the maintenance of ATP despite the loss of aerobic metabolism in a manner that prevents a disruption of ionic homeostasis. Instead, the abilities to maintain a hypometabolic state with low ATP and tolerate large disturbances in ionic status appear to contribute to the higher anoxia tolerance of adults. Furthermore, metabolomics experiments support this notion by showing that larvae had higher metabolic rates during the initial 30 min of anoxia and that protective metabolites were upregulated in adults but not larvae. Lastly, I investigated the genetic variation in anoxia tolerance using a genome wide association study (GWAS) to identify target genes associated with anoxia tolerance. Results from the GWAS also suggest mechanisms related to protection from ionic and oxidative stress, in addition to a protective role for immune function. / Dissertation/Thesis / Results of GWAS for Adults Exposed to 6 H of Anoxia / Results of GWAS for Larvae Exposed to 1 H of Anoxia / Doctoral Dissertation Evolutionary Biology 2018

<p>For many years, researchers have developed ways to diagnose degenerative disease in the retina by utilizing multiple gene analysis techniques. Retinitis pigmentosa (RP) disease can cause either partially or totally blindness in adults. For that reason, it is crucial to find a way to pinpoint the causes in order to develop a proper medication or treatment. One of the common methods is genome-wide analysis (GWA). However, it cannot fully identify the genes that are indirectly related to the changes in eye size. In this research, RNA sequencing (RNA-seq) analysis is used to link the phenotype to genotype, creating a pool of candidate genes that might associate with the RP. This will support future research in finding a therapy or treatment to cure such disease in human adults.</p> <p><br></p> <p>Using the Drosophila Genetic Reference Panel (DGRP) – a gene reference panel of fruit fly – two types of datasets are involved in this analysis: eye-size data and gene expression data with two replicates for each strain. This allows us to create a phenotype-genotype map. In other words, we are trying to trace the genes (genotype) that exhibit the RP disease guided by comparing their eye size (phenotype). The basic idea of the algorithm is to discover the best replicate combination that maximizes the correlation between gene expression and eye-size. Since there are 2N possible replicate combinations, where N is the number of selected strains, the original implementation of sequential algorithm was computationally intensive.</p> <p><br></p> <p>The original idea of finding the best replicate combination was proposed by Nguyen et al. (2022). In this research, however, we restructured the algorithms to distribute the tasks of finding the best replicate combination and run them in parallel. The implementation was done using the R programming language, utilizing doParallel and foreach packages, and able to execute on a multicore machine. The program was tested on both a laptop and a server, and the experimental results showed an outstanding improvement in terms of the execution time. For instance, while using 32 processes, the results reported up to 95% reduction in execution time when compared with the sequential version of the code. Furthermore, with the increment of computational capabilities, we were able to explore and analyze more extreme eye-size lines using three eye-size datasets representing different phenotype models. This further improved the accuracy of the results where the top candidate genes from all cases showed connection to RP.</p>

<p>The goal of this thesis is to algorithmically identify candidate modifiers for <i>retinitis pigmentosa</i> (RP) to help improve therapy and predictions for this genetic disorder that may lead to a complete loss of vision. A current research by (Chow et al., 2016) focused on the genetic contributors to RP by trying to recognize a correlation between genetic modifiers and phenotypic variation in female <i>Drosophila melanogaster</i>, or fruit flies. In comparison to the genome-wide association analysis carried out in Chow et al.’s research, this study proposes using a K-Means clustering algorithm on RNA expression data to better understand which genes best exhibit characteristics of the RP degenerative model. Validating this algorithm’s effectiveness in identifying suspected genes takes priority over their classification.</p><p>This study investigates the linear relationship between <i>Drosophila </i>eye size and genetic expression to gather statistically significant, strongly correlated genes from the clusters with abnormally high or low eye sizes. The clustering algorithm is implemented in the R scripting language, and supplemental information details the steps of this computational process. Running the mean eye size and genetic expression data of 18,140 female <i>Drosophila</i> genes and 171 strains through the proposed algorithm in its four variations helped identify 140 suspected candidate modifiers for retinal degeneration. Although none of the top candidate genes found in this study matched Chow’s candidates, they were all statistically significant and strongly correlated, with several showing links to RP. These results may continue to improve as more of the 140 suspected genes are annotated using identical or comparative approaches.</p>